Triple

T9522337
Position Surface form Disambiguated ID Type / Status
Subject Province of Almería E229672 entity
Predicate mountainRange P648 FINISHED
Object Sierra Nevada E149694 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sierra Nevada | Statement: [Province of Almería, mountainRange, Sierra Nevada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sierra Nevada
Context triple: [Province of Almería, mountainRange, Sierra Nevada]
  • A. Sierra Nevada chosen
    Sierra Nevada is a prominent mountain range in southern Spain known for its high peaks, ski resorts, and inclusion in a national park.
  • B. Sierra Nevada
    Sierra Nevada is a major mountain range in the western United States known for its dramatic granite peaks, extensive forests, and iconic natural landmarks such as Yosemite National Park and Lake Tahoe.
  • C. Sierra
    Sierra is one of the central "Actives" in the TV series *Dollhouse*, known for her complex backstory and evolving sense of identity amid the show's mind-wiping technology.
  • D. Sierra
    Sierra is the Andean highland natural region of Peru, characterized by mountainous terrain, high plateaus, and a cool climate.
  • E. Sierra
    Sierra is a residential neighborhood within the master-planned Great Park Neighborhoods community in Irvine, California.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca847870a881909d8d751a7d29da39 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd989788e4819086c235bf37a56b04 completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c1f10748190a36d2092d593be97 completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 7:59 p.m.